
Active Visual Analytics: Assisted Data Discovery in Interactive Visualizations via Active Search
We propose the Active Visual Analytics technique (ActiveVA), an augmenta...
read it

Competing Models: Inferring Exploration Patterns and Information Relevance via Bayesian Model Selection
Analyzing interaction data provides an opportunity to learn about users,...
read it

Efficient Nonmyopic Bayesian Optimization via OneShot MultiStep Trees
Bayesian optimization is a sequential decision making framework for opti...
read it

GPIRT: A Gaussian Process Model for Item Response Theory
The goal of item response theoretic (IRT) models is to provide estimates...
read it

Efficient nonmyopic Bayesian optimization and quadrature
Finitehorizon sequential decision problems arise naturally in many mach...
read it

DVAE: A Variational Autoencoder for Directed Acyclic Graphs
Graph structured data are abundant in the real world. Among different gr...
read it

Automated Model Selection with Bayesian Quadrature
We present a novel technique for tailoring Bayesian quadrature (BQ) to m...
read it

Efficient nonmyopic active search with applications in drug and materials discovery
Active search is a learning paradigm for actively identifying as many me...
read it

Learning and Anticipating Future Actions During Exploratory Data Analysis
The goal of visual analytics is to create a symbiosis between human and ...
read it

An Improved Bayesian Framework for Quadrature of Constrained Integrands
Quadrature is the problem of estimating intractable integrals, a problem...
read it

Active Search for Sparse Signals with Region Sensing
Autonomous systems can be used to search for sparse signals in a large s...
read it

Exact Sampling from Determinantal Point Processes
Determinantal point processes (DPPs) are an important concept in random ...
read it

Anomaly Detection and Removal Using NonStationary Gaussian Processes
This paper proposes a novel Gaussian process approach to fault removal i...
read it

Differentially Private Bayesian Optimization
Bayesian optimization is a powerful tool for finetuning the hyperparam...
read it

Sampling for Inference in Probabilistic Models with Fast Bayesian Quadrature
We propose a novel sampling framework for inference in probabilistic mod...
read it

Propagation Kernels
We introduce propagation kernels, a general graphkernel framework for e...
read it

Submodularity in Batch Active Learning and Survey Problems on Gaussian Random Fields
Many realworld datasets can be represented in the form of a graph whose...
read it

Bayesian Optimal Active Search and Surveying
We consider two active binaryclassification problems with atypical obje...
read it
Roman Garnett
is this you? claim profile